ARTIFICIAL INTELLIGENCE 2006

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ARTIFICIAL INTELLIGENCE2006

• Ira Pohl
• TIM Feb 23, 2006

2
Talk

• What is AI?
• A brief history
• Use in Industry
• My work
• Future

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What is AI?

• AI a science/engineering of intelligence
• In analogy to aeronautical engineering/flying
• computer produces an intelligent result
• AI model of human/cognitive system
• Is done as a theory of human intelligence
• - computer mimics human intelligence

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Acting humanly Turing Test

• Turing (1950) "Computing machinery and
  intelligence"
• "Can machines think?" ? "Can machines behave
  intelligently?"
• Operational test for intelligent behavior the
  Imitation Game
  
• Predicted that by 2000, a machine might have a
  30 chance of fooling a lay person for 5 minutes
• Anticipated all major arguments against AI in
  following 50 years
• Loebner Prize //www.loebner.net/Prizef/loebner-
  prize.html

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Thinking humanly cognitive modeling

• 1960s "cognitive revolution" information-processi
  ng psychology Newell and Simon GPS
  
• Requires scientific theories of internal
  activities of the brain
  
• -- How to validate? Requires
• 1) Predicting and testing behavior of human
  subjects (top-down)
• or 2) Direct identification from neurological
  data (bottom-up)
  

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Thinking rationally "laws of thought"

• Several Greek schools developed various forms of
  logic notation and rules of derivation for
  thoughts may or may not have proceeded to the
  idea of mechanization
• Direct line through mathematics and philosophy to
  modern AI
  -Boole
• Kleene, Church, Turing McCarthy, Robinson

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AI prehistory

• Philosophy Logic, methods of reasoning, mind as
  physical system foundations of learning,
  language, rationality
• Mathematics Formal representation and proof
  algorithms, computation, (un)decidability,
  (in)tractability, probability
• Economics/OR utility, decision theory
• Neuroscience physical substrate for mental
  activity
• Psychology phenomena of perception and motor
  control, experimental techniques
• Computer Science building fast computers,
  algorithms
• Linguistics knowledge representation, grammar

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Abridged history of AI

• 1943 McCulloch Pitts Boolean circuit
  model of brain
• 1950 Turing's "Computing Machinery and
  Intelligence"
• 1956 Dartmouth meeting "Artificial
  Intelligence" adopted
• 1950s Early AI programs, including Samuel's
  checkers program, Newell Simon's Logic
  Theorist, Gelernter's Geometry Engine
• 1965 Robinson's complete algorithm for logical
  reasoning
• 196979 Early development of knowledge-based
  systems
• 1970 Industrial Robotics painting/welding
• 1980 AI industry -Symbolics
• 1985 The emergence of modern learning
• 2003 iRobot roomba- everyday robotics

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State of the art

• Deep Blue defeated the reigning world chess
  champion Garry Kasparov in 1997 -IBM
• Proved a mathematical conjecture (Robbins
  conjecture) unsolved for decades -OTTER
• In 1995 No hands across America (driving
  autonomously 98 of the time from Pittsburgh to
  San Diego) CMU
• In 1998 720,000 industrial robots (UNIMATE 1963)
• 2003 ASE NASA's on-board autonomous planning
  program controlled the scheduling of operations
  for a spacecraft EOS1
• Roomba- 2003 credible home robot

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Achievements

• LISP, Time Sharing
• Games early spacewar games 1962 first computer
  video game PDP1
• Intellectual Games mastery in Chess, checkers,
  othello, backgammon, scrabble-
• But not(yet) Go or Poker
• MACSYMA Mathematica, MATLAB
• DENDRAL(chemistry, medicine experts)
• Robotics
• Speech and Handwriting recognition

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Basic Methods

• Logic All men are mortal
• Formal, with inference rules -McCarthy
• Heuristic search, ad-hoc domain specific
  rules Michie, Nilsson, Pohl
• Learning adaptive Haussler, Warmuth
• Knowledge Frameworks(KE, Productions) Minsky,
  Schank

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Game Tree alpha-beta
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Heuristic search

• Let us suppose that we have one piece of
  information a heuristic function
• h(n) 0, n a goal node
• h(n) gt 0, n not a goal node
• we can think of h(n) as a guess as to how far n
  is from the goal
• Best-First-Search(state,h)
• nodes lt- MakePriorityQueue(state, h(state))
• while (nodes ! empty)
• node pop(nodes)
• if (GoalTest(node) succeeds return node
• for each child in succ(node)
• nodes lt- push(child,h(child))
• return failure

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Michie 8-puzzle

• 8-puzzle h(n) tiles out of place
• 1 2 3
• 8 4
• 7 6 5 goal
• N! For N sliding tiles

1 2 3
8 6
7 5 4
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Search Performance
Heuristic 1 Tiles out of place
Heuristic 1 Manhattan distance
8-Square
Manhattan distance .total number of horizontal
and vertical moves required to move all tiles to
their position in the goal state from their
current position.
0 1 2
3 4 5
6 7 8
3 2 5
7 1
4 6 8
h1 7 h2 211211109
gt Choice of heuristic is critical to heuristic
search algorithm performance.
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My Work

• BIDIRECTIONAL SEARCH -1969-
• Focused Search G node with Politowski 1984
• Piecewise search with Ratner 1985
• Pohl-Warnsdorf method Hamiltonians
• A adversary analysis- 1969-
• Regular degree 3 recursively described
  adversaries with Stockmeyer 2004

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Games

• Games Laird games are a testbed for
  comprehensive AI such as characters in FAÇADE
  or opponents and teammates in Madden Football
  Why?
• Funge has a textbook will teach here next
  quarter

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Ikuni - Funge

• John Funge is a co-founder and one of the lead
  scientists at a new Silicon Valley based company
  (ikuni)focusing on AI effects for computer
  entertainment. John successfully developed a new
  approach to high-level control of characters in
  games and animation. John is the author of
  numerous technical papers and two books on Game
  AI, including his new book Artificial
  Intelligence for Computer Games An Introduction.
  
• His current research interests include computer
  games, machine learning, knowledge representation
  and new democratic methods.

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A Real Psychiatrist

• ELIZA Weizenbaum
• Why Colby needed for autism, prisoners ,
• Why not Weizenbaum alien and unfeeling
  lacking human empathy
• Passing T-Test still seems 50 years off

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Conclusions

• AI has been very successful and in many
  instances(robotics, speech) developed as a
  separate discipline
• Assisted expertise such as Chemistry experts
  systems (Wipke) and math experts MATLAB ,
  mathematica
• Failures general AI, common sense reasoning
  (Emperors new mind Penrose)
• Is it desirable?